Assistant Professor of Statistics

University of Nebraska, Lincoln


Susan Vanderplas is an assistant professor in the Statistics Department at University of Nebraska, Lincoln, researching the perception of statistical charts and graphs. She also works with the Center for Statistical Applications in Forensic Evidence (CSAFE) at Iowa State University, developing statistical methods for examination of bullets, cartridges, and footwear.

In her spare time (hah) she likes to sew, cross-stitch mildly off-color sayings, and bake things (usually badly).


  • Forensic Statistics
  • Statistical Graphics
  • Computer Vision
  • Human Perception
  • Machine Learning
  • Statistical Computing


  • PhD in Statistics, 2015

    Iowa State University

  • MS in Statistics, 2011

    Iowa State University

  • BSc in Psychology and Applied Mathematical Sciences, 2009

    Texas A&M University



Assistant Professor

University of Nebraska, Lincoln

Jan 2020 – Present Lincoln, NE
Research topics including: statistical graphics, human perception, computer vision, statistical forensics (bullets, shoes), and fun datasets.

Assistant Research Professor

Iowa State University

Mar 2018 – Dec 2019 Ames, Iowa
Develop statistical methods applicable to forensic pattern evidence, which generally is stored as image data. Assist with the development of open-source software packages, such as x3ptools and bulletxtrctr to make the methods accessible to the forensics community. Design and execute experiments that provide data for reference databases to support future work in statistical forensics. Conduct outreach activities to increase awareness of CSAFE’s research and to promote the use of statistics in forensics contexts.

Statistical Analyst

Nebraska Public Power District

Aug 2015 – Feb 2018 Nebraska

Conduct statistical analyses to support business decisions. Serve as a resource to shape future directions in data science and analytics across the district. Develop interactive reporting, data visualizations, and other software to support business needs. Analytics activities include prediction of electrical demand and employee turnover, assessment of equipment reliability and operational risk due to weather or changing environmental conditions, and modeling of employee compensation and completion time for mission-critical scheduling tasks.

Develop an internal training process for data science, leveraging online resources and cooperative learning groups to allow professionals to learn R, data visualization using ggplot2, data cleaning using the tidyverse, reporting using rmarkdown, basic statistical modeling and machine learning techniques while integrating those skills into their current position responsibilities.

Part-time position Mar-2018 to present.


Statistical Consultant

VanderPlas Consulting

May 2014 – Present

Develop web applications to present data and statistical analyses to targeted groups. Examples: